GravitySpace: Tracking Users and Their Poses in a Smart Room Using a Pressure-Sensing Floor

Figure 1

GravitySpace recognizes people and objects and reconstructs their 3D poses based solely on the pressure marks all objects leave on the floor. For displaying output, we use a mirror-metaphor to show on the floor how GravitySpace identifies users and tracks their location and poses.

Abstract

We explore how to track people and furniture based on a high-resolution pressure-sensitive floor. Gravity pushes people and objects against the floor, causing them to leave imprints of pressure distributions across the surface. While the sensor is limited to sensing direct contact with the surface, we can sometimes conclude what takes place above the surface, such as users’ poses or collisions with virtual objects. We demonstrate how to extend the range of this approach by sensing through passive furniture that propagates pressure to the floor. To explore our approach, we have created an 8 m2 back-projected floor prototype, termed GravitySpace, a set of passive touch-sensitive furniture, as well as algorithms for identifying users, furniture, and poses. Pressure-based sensing on the floor offers four potential benefits over camera- based solutions: (1) it provides consistent coverage of rooms wall-to-wall, (2) is less susceptible to occlusion between users, (3) allows for the use of simpler recognition algorithms, and (4) intrudes less on users’ privacy.